IMPROVE CONSERVATION MANAGEMENT THROUGH MACHINE LEARNING & REMOTE SENSING
Aiforgood Asia, an NGO focused on AI and technology for environmental and social governance (ESG) projects, partnered with Crayon, an IT service specialist, to address the challenge of forest degradation in Mu Cang Chai forest, Vietnam. The forest is home to endangered species like the western black gibbon, and degradation is caused by illegal cardamon cultivation.
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The project aimed to develop a computer vision-based solution that utilized remote sensing and machine learning to detect cardamon cultivation in satellite imagery. Fauna & Flora, an international conservation charity, provided ground truth data for the project.
APPROACH
The project showed that remote sensing and machine learning could effectively detect cardamon cultivation in satellite imagery under certain conditions. The success of this project could help preserve the forest habitat of critically endangered species like the western black gibbon.
OUTCOME
The team faced challenges in obtaining cost-efficient remote sensing data for the model, but they eventually used high-resolution images from WorldView-2. The model achieved a high pixel within-sample accuracy of approximately 96%.
NEXT STEPS
The success of this project demonstrates the potential of AI and remote sensing technologies in supporting conservation efforts and addressing complex environmental challenges. It also highlights the importance of collaboration between businesses, organizations, and NGOs to create sustainable solutions for protecting biodiversity and the environment.
PROJECT COLLABORATORS
